Theorem (Theorem 6.2 in [1]}) 
Let \(\widehat{f}(\cdot )\)  denote the non-linear predictor defined in (REF ). Let \(P\)  be any distribution (with possibly unbounded covariates) satisfying \(\Vert Y\Vert _{L_{\infty }} \le m\) . Then, for any \(d, n > 0\) , the following holds:
\(\operatorname{\mathbb {E}}R(\widehat{f}(X)) - \inf \limits _{\omega \in \mathbb {R}^d}R(\omega )\lesssim \frac{dm^{2}}{n}.\) 

